Electrochemical Corrosion of Steels in Distillery Effluent

The present work relates to the corrosivity of distillery effluent and corrosion performance of mild steel and stainless steels SS304L, SS316L, and 2205. The report presents the results and conclusions drawn on the basis of (i) electrochemical polarization tests performed in distillery effluent and laboratory prepared solutions having composition similar to that of the effluent (ii) the surface examination by scanning electron microscope (SEM) of the corroded steel samples. It is observed that pH and presence of chloride, phosphate, calcium, nitrite and nitrate in distillery effluent enhance corrosion, whereas presence of sulphate and potassium inhibits corrosion. Among the materials tested, mild steel is observed to experience maximum corrosion followed by stainless steels SS304L, SS316L, and 2205.

Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier

Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Finite Element Modeling of Stockbridge Damper and Vibration Analysis: Equivalent Cable Stiffness

Aeolian vibrations are the major cause for the failure of conductor cables. Using a Stockbridge damper reduces these vibrations and increases the life span of the conductor cable. Designing an efficient Stockbridge damper that suits the conductor cable requires a robust mathematical model with minimum assumptions. However it is not easy to analytically model the complex geometry of the messenger. Therefore an equivalent stiffness must be determined so that it can be used in the analytical model. This paper examines the bending stiffness of the cable and discusses the effect of this stiffness on the natural frequencies. The obtained equivalent stiffness compensates for the assumption of modeling the messenger as a rod. The results from the free vibration analysis of the analytical model with the equivalent stiffness is validated using the full scale finite element model of the Stockbridge damper.

Grain Size Characteristics and Sediments Distribution in the Eastern Part of Lekki Lagoon

A total of 20 bottom sediment samples were collected from the Lekki Lagoon during the wet and dry season. The study was carried out to determine the textural characteristics, sediment distribution pattern and energy of transportation within the lagoon system. The sediment grain sizes and depth profiling was analyzed using dry sieving method and MATLAB algorithm for processing. The granulometric reveals fine grained sand both for the wet and dry season with an average mean value of 2.03 ϕ and -2.88 ϕ, respectively. Sediments were moderately sorted with an average inclusive standard deviation of 0.77 ϕ and -0.82 ϕ. Skewness varied from strongly coarse and near symmetrical 0.34- ϕ and 0.09 ϕ. The kurtosis average value was 0.87 ϕ and -1.4 ϕ (platykurtic and leptokurtic). Entirely, the bathymetry shows an average depth of 4.0 m. The deepest and shallowest area has a depth of 11.2 m and 0.5 m, respectively. High concentration of fine sand was observed at deep areas compared to the shallow areas during wet and dry season. Statistical parameter results show that the overall sediments are sorted, and deposited under low energy condition over a long distance. However, sediment distribution and sediment transport pattern of Lekki Lagoon is controlled by a low energy current and the down slope configuration of the bathymetry enhances the sorting and the deposition rate in the Lekki Lagoon.

Factors Affecting the Wages of Native Workers in Thailand's Construction Industry

This research studies the factors influencing the wages of native workers in Thailand's construction industry. The sample used comprised some 156 native construction workers from Songkhla Province, Thailand. The utilized research instrument was a questionnaire, with the data being analyzed according to frequency, percentage, and regression analysis. The results revealed that in general, native Thai construction workers are generally married males aged between 26 and 37 years old. They typically have four to six years of education, are employed as laborers with an average salary of 4,000–9,200 baht per month, and have fewer than five years of work experience. Most Thai workers work five days a week. Each establishment typically has 10–30 employees, with fewer than 10 of these being migrant workers in general. Most Thai workers are at a 20% to 40% risk from work, and they have never changed employer. The average wage of Thai workers was found to be 10,843.03 baht per month with a standard deviation of 4,898.31 baht per month. Hypothesis testing revealed that position, work experience, and the number of times they had switched employer were the factors most affecting the wages of native Thai construction workers. These three factors alone explain the salaries of Thai construction workers at 51.9%.  

A Proposal for U-City (Smart City) Service Method Using Real-Time Digital Map

Recently, technologies based on three-dimensional (3D) space information are being developed and quality of life is improving as a result. Research on real-time digital map (RDM) is being conducted now to provide 3D space information. RDM is a service that creates and supplies 3D space information in real time based on location/shape detection. Research subjects on RDM include the construction of 3D space information with matching image data, complementing the weaknesses of image acquisition using multi-source data, and data collection methods using big data. Using RDM will be effective for space analysis using 3D space information in a U-City and for other space information utilization technologies.

Effect of Bacillus subtilis Pb6 on Growth and Gut Microflora in Clostridium perfringens Challenged Broilers

The objective of current study was to investigate the effect of Bacillus subtilis PB6 (CloSTAT) as a probiotic in broilers. The corn-soybean based diet was divided into four treatment groups; T1 (basal diet with no probiotic and no Clostridium perfringens); T2 (basal diet challenged with C. perfringens without probiotic); T3 (basal diet challenged with C. perfringens having 0.05% probiotic); T4 (basal diet challenged with C. perfringens having 0.1% probiotic). Every treatment group had four replicates with 24 birds each. Body weight and feed intake were measured on weekly basis, while ileal bacterial count was recorded on day-28 following Clostridium perfringens challenge. The 0.1% probiotic treatment showed 7.2% increase in average feed intake (P=0.05) and 8% increase in body weight compared to T2. In 0.1% treatment body weight was 5% higher than T3 (P=0.02). It was also observed that 0.1% treatment had improved feed conversion ratio (1.77) on 6th week. No effect of treatment was observed on mortality and ileal bacterial count. The current study indicated that 0.1% use of probiotic had positive response in C. perfringens challenged broilers.

Inner Quality Parameters of Rapeseed (Brassica napus) Populations in Different Sowing Technology Models

Demand on plant oils has increased to an enormous extent that is due to the change of human nutrition habits on the one hand, while on the other hand to the increase of raw material demand of some industrial sectors, just as to the increase of biofuel production. Besides the determining importance of sunflower in Hungary the production area, just as in part the average yield amount of rapeseed has increased among the produced oil crops. The variety/hybrid palette has changed significantly during the past decade. The available varieties’/hybrids’ palette has been extended to a significant extent. It is agreed that rapeseed production demands professionalism and local experience. Technological elements are successive; high yield amounts cannot be produced without system-based approach. The aim of the present work was to execute the complex study of one of the most critical production technology element of rapeseed production, that was sowing technology. Several sowing technology elements are studied in this research project that are the following: biological basis (the hybrid Arkaso is studied in this regard), sowing time (sowing time treatments were set so that they represent the wide period used in industrial practice: early, optimal and late sowing time) plant density (in this regard reaction of rare, optimal and too dense populations) were modelled. The multifactorial experimental system enables the single and complex evaluation of rapeseed sowing technology elements, just as their modelling using experimental result data. Yield quality and quantity have been determined as well in the present experiment, just as the interactions between these factors. The experiment was set up in four replications at the Látókép Plant Production Research Site of the University of Debrecen. Two different sowing times were sown in the first experimental year (2014), while three in the second (2015). Three different plant densities were set in both years: 200, 350 and 500 thousand plants ha-1. Uniform nutrient supply and a row spacing of 45 cm were applied. Winter wheat was used as pre-crop. Plant physiological measurements were executed in the populations of the Arkaso rapeseed hybrid that were: relative chlorophyll content analysis (SPAD) and leaf area index (LAI) measurement. Relative chlorophyll content (SPAD) and leaf area index (LAI) were monitored in 7 different measurement times.

An Investigation on Ultrasonic Pulse Velocity of Hybrid Fiber Reinforced Concretes

Because of the easy applying and not costing too much, ultrasonic pulse velocity (UPV) is one of the most used non-destructive techniques to determine concrete characteristics along with impact-echo, Schmidt rebound hammer (SRH) and pulse-echo. This article investigates the relationship between UPV and compressive strength of hybrid fiber reinforced concretes. Water/cement ratio (w/c) was kept at 0.4 for all concrete mixes. Compressive strength of concrete was targeted at 35 MPa. UPV testing and compressive strength tests were carried out at the curing age of 28 days. The UPV of concrete containing steel fibers has been found to be higher than plain concrete for all the testing groups. It is decided that there is not a certain relationship between fiber addition and strength.

Prediction-Based Midterm Operation Planning for Energy Management of Exhibition Hall

Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.

Facial Recognition on the Basis of Facial Fragments

There are many articles that attempt to establish the role of different facial fragments in face recognition. Various approaches are used to estimate this role. Frequently, authors calculate the entropy corresponding to the fragment. This approach can only give approximate estimation. In this paper, we propose to use a more direct measure of the importance of different fragments for face recognition. We propose to select a recognition method and a face database and experimentally investigate the recognition rate using different fragments of faces. We present two such experiments in the paper. We selected the PCNC neural classifier as a method for face recognition and parts of the LFW (Labeled Faces in the Wild) face database as training and testing sets. The recognition rate of the best experiment is comparable with the recognition rate obtained using the whole face.

Numerical Solution of Manning's Equation in Rectangular Channels

When the Manning equation is used, a unique value of normal depth in the uniform flow exists for a given channel geometry, discharge, roughness, and slope. Depending on the value of normal depth relative to the critical depth, the flow type (supercritical or subcritical) for a given characteristic of channel conditions is determined whether or not flow is uniform. There is no general solution of Manning's equation for determining the flow depth for a given flow rate, because the area of cross section and the hydraulic radius produce a complicated function of depth. The familiar solution of normal depth for a rectangular channel involves 1) a trial-and-error solution; 2) constructing a non-dimensional graph; 3) preparing tables involving non-dimensional parameters. Author in this paper has derived semi-analytical solution to Manning's equation for determining the flow depth given the flow rate in rectangular open channel. The solution was derived by expressing Manning's equation in non-dimensional form, then expanding this form using Maclaurin's series. In order to simplify the solution, terms containing power up to 4 have been considered. The resulted equation is a quartic equation with a standard form, where its solution was obtained by resolving this into two quadratic factors. The proposed solution for Manning's equation is valid over a large range of parameters, and its maximum error is within -1.586%.

Simulation Study of Asphaltene Deposition and Solubility of CO2 in the Brine during Cyclic CO2 Injection Process in Unconventional Tight Reservoirs

A compositional reservoir simulation model (CMG-GEM) was used for cyclic CO2 injection process in unconventional tight reservoir. Cyclic CO2 injection is an enhanced oil recovery process consisting of injection, shut-in, and production. The study of cyclic CO2 injection and hydrocarbon recovery in ultra-low permeability reservoirs is mainly a function of rock, fluid, and operational parameters. CMG-GEM was used to study several design parameters of cyclic CO2 injection process to distinguish the parameters with maximum effect on the oil recovery and to comprehend the behavior of cyclic CO2 injection in tight reservoir. On the other hand, permeability reduction induced by asphaltene precipitation is one of the major issues in the oil industry due to its plugging onto the porous media which reduces the oil productivity. In addition to asphaltene deposition, solubility of CO2 in the aquifer is one of the safest and permanent trapping techniques when considering CO2 storage mechanisms in geological formations. However, the effects of the above uncertain parameters on the process of CO2 enhanced oil recovery have not been understood systematically. Hence, it is absolutely necessary to study the most significant parameters which dominate the process. The main objective of this study is to improve techniques for designing cyclic CO2 injection process while considering the effects of asphaltene deposition and solubility of CO2 in the brine in order to prevent asphaltene precipitation, minimize CO2 emission, optimize cyclic CO2 injection, and maximize oil production.

Research on Urban Point of Interest Generalization Method Based on Mapping Presentation

Without taking account of the attribute richness of POI (point of interest) data and spatial distribution limited by roads, a POI generalization method considering both attribute information and spatial distribution has been proposed against the existing point generalization algorithm merely focusing on overall information of point groups. Hierarchical characteristic of urban POI information expression has been firstly analyzed to point out the measurement feature of the corresponding hierarchy. On this basis, an urban POI generalizing strategy has been put forward: POIs urban road network have been divided into three distribution pattern; corresponding generalization methods have been proposed according to the characteristic of POI data in different distribution patterns. Experimental results showed that the method taking into account both attribute information and spatial distribution characteristics of POI can better implement urban POI generalization in the mapping presentation.

Role of Facade in Sustainability Enhancement of Contemporary Iranian Buildings

A growing demand for sustainability makes sustainability as one of the significant debates of nowadays. Energy saving is one of the main criteria to be considered in the context of sustainability. Reducing energy use in buildings is one of the most important ways to reduce humans’ overall environmental impact. Taking this into consideration, study of different design strategies, which can assist in reducing energy use and subsequently improving the sustainability level of today's buildings would be an essential task. The sustainability level of a building is highly affected by the sustainability performance of its components. One of the main building components, which can have a great impact on energy saving and sustainability level of the building, is its facade. The aim of this study is to investigate on the role of facade in sustainability enhancement of the contemporary buildings of Iran. In this study, the concept of sustainability in architecture, the building facades, and their relationship to sustainability are explained briefly. Following that, a number of contemporary Iranian buildings are discussed and analyzed in terms of different design strategies used in their facades in accordance to the sustainability concepts. The methods used in this study are descriptive and analytic. The results of this paper would assist in generating a wider vision and a source of inspiration for the current designers to design and create environmental and sustainable buildings for the future.

Techno-Economic Analysis of Motor-Generator Pair System and Virtual Synchronous Generator for Providing Inertia of Power System

With the increasing of the penetration of renewable energy in power system, the whole inertia of the power system is declining, which will endanger the frequency stability of the power system. In order to enhance the inertia, virtual synchronous generator (VSG) has been proposed. In addition, the motor-generator pair (MGP) system is proposed to enhance grid inertia. Both of them need additional equipment to provide instantaneous energy, so the economic problem should be considered. In this paper, the basic working principle of MGP system and VSG are introduced firstly. Then, the technical characteristics and economic investment of MGP/VSG are compared by calculation and simulation. The results show that the MGP system can provide same inertia with less cost than VSG.

Effect of Manganese Doping on Ferrroelectric Properties of (K0.485Na0.5Li0.015)(Nb0.98V0.02)O3 Lead-Free Piezoceramic

Alkaline niobate (Na0.5K0.5)NbO3 ceramic system has attracted major attention in view of its potential for replacing the highly toxic but superior lead zirconate titanate (PZT) system for piezoelectric applications. Recently, a more detailed study of this system reveals that the ferroelectric and piezoelectric properties are optimized in the Li- and V-modified system having the composition (K0.485Na0.5Li0.015)(Nb0.98V0.02)O3. In the present work, we further study the pyroelectric behaviour of this composition along with another doped with Mn4+. So, (K0.485Na0.5Li0.015)(Nb0.98V0.02)O3 + x MnO2 (x = 0, and 0.01 wt. %) ceramic compositions were synthesized by conventional ceramic processing route. X-ray diffraction study reveals that both the undoped and Mn4+-doped ceramic samples prepared crystallize into a perovskite structure having orthorhombic symmetry. Dielectric study indicates that Mn4+ doping has little effect on both the Curie temperature (Tc) and tetragonal-orthorhombic phase transition temperature (Tot). The bulk density, room-temperature dielectric constant (εRT), and room-c The room-temperature coercive field (Ec) is observed to be lower in Mn4+ doped sample. The detailed analysis of the P-E hysteresis loops over the range of temperature from about room temperature to Tot points out that enhanced ferroelectric properties exist in this temperature range with better thermal stability for the Mn4+ doped ceramic. The study reveals that small traces of Mn4+ can modify (K0.485Na0.5Li0.015)(Nb0.98V0.02)O3 system so as to improve its ferroelectric properties with good thermal stability over a wide range of temperature.

Influence of Temperature and Precipitation Changes on Desertification

The purpose of this paper was separation and study of the part of structure regime, which directly affects the process of desertification. A simple scheme was prepared for the assessment of desertification process; surface air temperature and precipitation for the years of 1936-2009 were analyzed.  The map of distribution of the Desertification Contributing Coefficient in the territory of Georgia was compiled. The simple scheme for identification of the intensity of the desertification contributing process has been developed and the illustrative example of its practical application for the territory of Georgia has been conducted.

Clustering Categorical Data Using the K-Means Algorithm and the Attribute’s Relative Frequency

Clustering is a well known data mining technique used in pattern recognition and information retrieval. The initial dataset to be clustered can either contain categorical or numeric data. Each type of data has its own specific clustering algorithm. In this context, two algorithms are proposed: the k-means for clustering numeric datasets and the k-modes for categorical datasets. The main encountered problem in data mining applications is clustering categorical dataset so relevant in the datasets. One main issue to achieve the clustering process on categorical values is to transform the categorical attributes into numeric measures and directly apply the k-means algorithm instead the k-modes. In this paper, it is proposed to experiment an approach based on the previous issue by transforming the categorical values into numeric ones using the relative frequency of each modality in the attributes. The proposed approach is compared with a previously method based on transforming the categorical datasets into binary values. The scalability and accuracy of the two methods are experimented. The obtained results show that our proposed method outperforms the binary method in all cases.

A Computational Cost-Effective Clustering Algorithm in Multidimensional Space Using the Manhattan Metric: Application to the Global Terrorism Database

The increasing amount of collected data has limited the performance of the current analyzing algorithms. Thus, developing new cost-effective algorithms in terms of complexity, scalability, and accuracy raised significant interests. In this paper, a modified effective k-means based algorithm is developed and experimented. The new algorithm aims to reduce the computational load without significantly affecting the quality of the clusterings. The algorithm uses the City Block distance and a new stop criterion to guarantee the convergence. Conducted experiments on a real data set show its high performance when compared with the original k-means version.